Introduction
This study is not intended to give advice to state or local
governments. This should be done by epidemiologists, who use
sophisticated models to predict and advise.
This study is intended to give the general public and local
governments a transparent and effective overview about the current state
of COVID-19 for most states in the continental US and their ten most
populous counties.
To understand the current situation the past needs to be referenced
as a benchmark. Therefore, this study does not only presents the current
values of Accumulated Cases, New Cases, and currently Active Cases, it
also shows the time trend of these measures.
The study is based on an authoritative data source: the New York Times. For
each of the counties and for the state as a whole, the Accumulated Cases
and daily New Cases are extracted from this data base and reported
similar to other publications (see Sections 1 and 2 for each county and
the state as a whole).
However, focusing on Accumulated Cases is not effective, because this
count includes cases of already recovered patients or patients that have
died. Consequently, the focus of this study is on an estimate for the
currently Active Cases (see Section 3 for each county and and the state
as a whole).
The Active Cases reflect the true danger in the current situation,
since New Cases are strongly correlated to Active Case. The more Active
Cases there are, the greater the chances of new infections, leading to
more New Cases.
A transparent and simple model is used to estimate Active Cases. The
model is based on the assumption that it takes in average 14 days to
recover from a COVID-19 infection. Estimates of medical experts vary
between 10 and 20+ days therefore 14 days seems to be reasonable.
To predict the Active Cases for any day, the Active Cases of the
previous day are used as a base. Then New Cases are added, and the
recovered cases and deaths are subtracted.
Since data on recovered cases are not very reliable, New Cases from
14 days ago are used as a proxy for recovered cases and deaths. This is
reasonable, since presumable all new patients from 14 days ago would be
either recovered or dead by the current day.
Consequently, the predicted Active Cases for any day are calculated
as the previous day’s Active Cases plus the New Cases from the current
day minus the New Cases 14 days ago (estimate for recovered and
deaths).
In order to get an idea about the trend of Active Cases, the daily
growth rate is also provided (see Section 4 for each county and the
state as a whole).
The study depends on currently available data. Since those are most
likely underestimated, all findings of the study should also be
considered as underestimated.
Maine
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This makes
it easier to see how the Accumulated Cases developed over time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases.
This makes it easier to see how the New Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Activ Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Cumberland County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This makes
it easier to see how the Accumulated Cases developed over time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases.
This makes it easier to see how the New Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
York County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This makes
it easier to see how the Accumulated Cases developed over time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Androscoggin
County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Kennebec County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Penobscot County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Waldo County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Franklin County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Oxford County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Sagadahoc County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
Somerset County
Accumulated Cases
(Active and Not-Active)
The chart below shows the accumulation of all reported COVID-19 cases
over time based on data from the New York Times.
To make the graph more readable, days with less than 10 Accumulated
Cases are not reported.
Accumulated Cases include currently Active Cases, as well as
recovered cases and deaths. Therefore, even when the pandemic is over,
the curve of Accumulated Cases will not return to zero. Instead it will
be entirely flat, but at a high level of cases. This makes it difficult
to interpret the number of Accumulated Cases. Therefore, in Sections 3
and 4 are more suitable measure - the currently Active Cases will be
introduced. The latter only includes infected patiens but neither
recovered patients nor deaths.
In the chart below, the black line graph represents the actual
Accumulated Cases as reported by the New York Times. The blue line graph
shows a trend and smoothes eratic changes of Accumulated Cases. This
makes it easier to see how the Accumulated Cases developed over
time.
The grey area (standard error) around the blue line graph is an
indicator for the quality of the smoothing estimate.
The slope of the black line graph represents the daily New Cases,
which are also displayed in the chart in the following section.
Daily New Cases
New Cases reflect how many patients were registered for the first
time as COVID-19 positive on a given day. When this measure approaches
zero and after all (or most) of the patients have recovered, the
COVID-19 crisis is over. New Cases are a good measure to determine how
well the general public participates in social distancing.
In the chart below, the black line graph represents the actual New
Cases as reported by the New York Times. The
blue line graph shows a trend and smoothes eratic changes of New
Cases. This makes it easier to see how the New
Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Predicted Active
Cases
The prediction of Active Cases presents a crucial measure when
evaluating the current COVID-19 situation. This is because every active
case has the potential to infect even more people and thus can
contribute to a more serious situation in the near future.
When the active cases decrease to a low level, then (and only then)
the danger of future exponential growth of COVID-19 can be considered as
small.
The model to predict the Active Cases is based on the assumption of a
recovery time of 14 days. Estimates of medical experts vary between 10
and 20+ days. Therefore, 14 days seems to be reasonable. The Active
Cases for any given day are predicted as follows:
Predicted Active Cases (previous day)
+ New Cases (current day)
- New Cases (14 days ago)
= Predicted Active Cases (current day)
New Cases (14 days ago) are used as an estimate for
recovered cases and deaths, because under the recovery time assumption
all people infected 14 days ago would have either recovered or died by
today.
Note, all components of the above equation are written in stone as
they are events from the distant past. The only exception are the New
Cases. The latter component - the New Cases - is the only component that
our society can control in the short run. New Cases stem from three
different sources:
- Very few New Cases stem from people who strictly obey the rules of
social distancing.
- New Cases also stem from the heroes of this pandemic such as
supermarket workers, delivery personnel, and medical staff. New Cases
from this source are mostly unavoidable.
- Numerous New Cases stem from those who either don’t know better,
consider the current situation as not serious, or are
self-centered.
The third source is both high in numbers and certainly avoidable.
Please, if you belong to the latter group, take a small
sacrifice (even if you are not convinced) to potentially save lives and
help to lower further damage to our economy.
In the chart below, the black line graph represents the Active Cases,
predicted as explained above. The blue line graph shows a trend and
smoothes eratic changes of these Active Cases over time. This makes it easier
to see how the Active Cases developed over time.
The grey area (standard error) around the blue graph is an indicator
for the quality of the smoothing estimate.
Daily %-Change in
Active Cases
The daily growth rate of Active Cases reflects our short-term success
or failure. Even a small percentage increases will lead to catastrophic
increases in active COVID-19 cases over a very short time. E.g., a daily
increase of 5% will double the active cases after only two weeks.
In order to decrease the Active Cases to a sustainable level, it is
not enough to reach a zero percentage change! Instead, a
negative double digit percentage change over several days is
needed.
In the chart below, the black line graph represents the daily growth
rates. The blue line graph shows a trend and smoothes eratic changes of
the daily growth rates over time. This makes it easier to see how the daily
percentage growth rates developed over time.
Summary Charts
